1. Field
The present invention relates to the field of wireless communications systems and, in particular, to determining spatial and temporal characteristics of signals received from transmitting wireless terminals.
2. Description of the Prior Art
Signal processing and a multiple antenna array can be used in a communication station (e.g., a base station) equipped with multiple antennas to either reject interference when receiving (e.g. on the uplink) or to deliver power in a spatially or spatio-temporally selective manner when transmitting (e.g., on the downlink). On the uplink, linear spatial processing can be used to apply amplitude and phase adjustments, typically but not necessarily in baseband, to each of the signals received at the antenna array elements. Such an adaptive smart antenna system can select (i.e., preferentially receive) the signals of interest while minimizing any signals or noise not of interest including interference. Such baseband amplitude and phase adjustment can be described by a complex valued weight, the receive weight, and the receive weights for all elements of the array can be described by a complex valued vector, the receive weight vector.
Similarly, the downlink signal is processed by adjusting the amplitude and phase of the baseband signals that are transmitted by each of the antennas of the antenna array. Such amplitude and phase control can be described by a complex valued weight, the transmit weight, and the weights for all elements of the array by a complex valued vector, the transmit weight vector. In some systems, the receive (and/or transmit) weights include temporal processing, and in such cases, the receive (and/or transmit) weights may be functions of frequency and applied in the frequency domain or, equivalently, functions of time applied as convolution kernels. Alternatively, each convolution kernel, if for sampled signals, may itself be described by a set of complex numbers, so that the vector of convolution kernels may be re-written as a complex values weight vector, which, for the case of there being M antennas and each kernel having K entries, would be a vector of KM entries.
System performance and the determination of weight vectors can be improved using knowledge of all remote user and interferer spatial signatures (or spatio-temporal signatures). The receive spatial signature and the receive spatio-temporal signature characterizes how the receiving array receives signals from a particular subscriber unit in the absence of any interference or other subscriber units. The transmit spatial signature and the transmit spatio-temporal signature of a particular remote user characterizes how the remote user receives signals from the transmitting station in the absence of any interference.
Spatial signatures can also be used to track the channels and movements of users and to track relative movement between users. The relative movement can be used as a measure of how close two users have come to each other. This information can be used for resource allocation decisions. For example, if two co-channel users come so close to together that their signals are difficult to resolve, then one of the users can be handed off to a different frequency.
An estimate of a spatial signature can be obtained from the correlation of the received signal from a particular user with the actual signal transmitted by the user. The actual transmitted signal can be determined using a known sequence, such as a training sequence or by estimating the signal. If only a training sequence is known, then the rest of the signal can be estimated based on the training sequence portion. A spatial signature determined from a simple correlation can be biased by interference from other users, noise and multipath effects. When two users are nearby and transmitting at about the same power it may not be possible to distinguish the two. When a high power user is transmitting near a low power user, it may not be possible to distinguish the low power user at all.